Computational protein design by accommodating flexibility and binding free energy in improving the affinity

Abstract

Computational structure-based protein design programs are becoming an increasingly important tool in molecular biology. The talk will review recent developments in algorithms for protein design, emphasizing how novel algorithms enable the use of more accurate biophysical models. The focus is on the relationship between protein flexibility and binding free energy and some useful hints for understanding when, and to what extent, flexibility. Lessons learned using molecular dynamics simulations and gaussian network model in designing DARPins (designed ankyrin repeat proteins), a genetically engineered antibody mimetic proteins, in HIV, dengue, and cancer targets will be discussed and concluded with a list of algorithmic challenges in computational protein design that we believe will be especially important for the design of therapeutic proteins.

Biography

Assoc. Prof. Dr. Vannajan Sanghiran Lee received her BSc (1994) in Chemistry from Chiang Mai University, Thailand and PhD (2001) in Pharmaceutical Sciences and Physical Chemistry from University of Missouri-Kansas City, USA under the scholarship from the Institute of Promotion and Development Science and Technology Project, Thailand. After that she received the Post Doctoral Scholarship (2002) from the Thailand Research Fund and worked at the Computational Chemistry Unit Cell (CCUC), Chulalongkorn University, Thailand. She worked as a lecturer and researcher in Computational Simulation and Modeling Laboratory (CSML), Department of Chemistry and Center for Innovation in Chemistry, Chiang Mai University, Chiang Mai, Thailand from 2001-2011. In 2010, she joined the school of pharmaceutical sciences, University Sains Malaysia as a visiting researcher. She presently works as a Assoc. Prof. at Department of chemistry, University of Malaya and as deputy head of Center of Theoretical and Computational Physics (TCP). Her present research interest includes computer-aided molecular modeling and computational chemistry using Molecular Dynamics (MD), Monte Carlo Simulations (MC), Quantum Mechanics (QM), Data Analytics and Machine Learning in diverse research and development fields such as biomolecular/material design.